Papers Coreference Resolution

Dynamic Entity Representations in Neural Language Models

Understanding a long document requires tracking how entities are introduced and evolve over time. We present a new type of language model, EntityNLM, that can explicitly model entities, dynamically update their represent…

Using Linguistic Features to Improve the Generalization Capability of Neural Coreference Resolvers

Coreference resolution is an intermediate step for text understanding. It is used in tasks and domains for which we do not necessarily have coreference annotated corpora. Therefore, generalization is of special importanc…

Collaborative Partitioning for Coreference Resolution

This paper presents a collaborative partitioning algorithm{---}a novel ensemble-based approach to coreference resolution. Starting from the all-singleton partition, we search for a solution close to the ensemble{'}s outp…

Robust Coreference Resolution and Entity Linking on Dialogues: Character Identification on TV Show Transcripts

This paper presents a novel approach to character identification, that is an entity linking task that maps mentions to characters in dialogues from TV show transcripts. We first augment and correct several cases of annot…

Towards Harnessing Memory Networks for Coreference Resolution

Coreference resolution task demands comprehending a discourse, especially for anaphoric mentions which require semantic information for resolving antecedents. We investigate into how memory networks can be helpful for co…

Improving Shared Argument Identification in Japanese Event Knowledge Acquisition

Event knowledge represents the knowledge of causal and temporal relations between events. Shared arguments of event knowledge encode patterns of role shifting in successive events. A two-stage framework was proposed for …

Improving coreference resolution with automatically predicted prosodic information

Adding manually annotated prosodic information, specifically pitch accents and phrasing, to the typical text-based feature set for coreference resolution has previously been shown to have a positive effect on German data…

Event Coreference Resolution by Iteratively Unfolding Inter-dependencies among Events

We introduce a novel iterative approach for event coreference resolution that gradually builds event clusters by exploiting inter-dependencies among event mentions within the same chain as well as across event chains. Am…

End-to-end Neural Coreference Resolution

We introduce the first end-to-end coreference resolution model and show that it significantly outperforms all previous work without using a syntactic parser or hand-engineered mention detector. The key idea is to directl…

Revisiting Selectional Preferences for Coreference Resolution

Selectional preferences have long been claimed to be essential for coreference resolution. However, they are mainly modeled only implicitly by current coreference resolvers. We propose a dependency-based embedding model …

Joint Learning for Event Coreference Resolution

While joint models have been developed for many NLP tasks, the vast majority of event coreference resolvers, including the top-performing resolvers competing in the recent TAC KBP 2016 Event Nugget Detection and Corefere…

Evaluation Metrics for Machine Reading Comprehension: Prerequisite Skills and Readability

Knowing the quality of reading comprehension (RC) datasets is important for the development of natural-language understanding systems. In this study, two classes of metrics were adopted for evaluating RC datasets: prereq…

Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures

An interesting aspect of structured prediction is the evaluation of an output structure against the gold standard. Especially in the loss-augmented setting, the need of finding the max-violating constraint has severely l…

Attention Is All You Need

The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an at…

Marmara Turkish Coreference Corpus and Coreference Resolution Baseline

We describe the Marmara Turkish Coreference Corpus, which is an annotation of the whole METU-Sabanci Turkish Treebank with mentions and coreference chains. Collecting eight or more independent annotations for each docume…

D\'etection de cor\'ef\'erences de bout en bout en fran\ccais (End-to-end coreference resolution for French)

Notre objectif est l{'}{\'e}laboration d{'}un syst{\`e}me de d{\'e}tection automatique de relations de cor{\'e}f{\'e}rence le plus g{\'e}n{\'e}ral possible, pour le traitement des anaphores pronominales et les cor{\'e}f{…

Entity Linking with people entity on Wikipedia

This paper introduces a new model that uses named entity recognition, coreference resolution, and entity linking techniques, to approach the task of linking people entities on Wikipedia people pages to their correspondin…

Coreference Resolution for Swedish and German using Distant Supervision

Docforia: A Multilayer Document Model

Lexical Features in Coreference Resolution: To be Used With Caution

Lexical features are a major source of information in state-of-the-art coreference resolvers. Lexical features implicitly model some of the linguistic phenomena at a fine granularity level. They are especially useful for…